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How to Make the τ-ARGUS Modular Method Applicable to Linked Tables

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Privacy in Statistical Databases (PSD 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5262))

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Abstract

The software package τ-ARGUS offers a very efficient algorithm for secondary cell suppression known as either HiTaS or the Modular approach. The method is well suited for the protection of up to 3-dimensional hierarchical tables. In practice, statistical agencies release multiple tabulations based on the same dataset. Usually these tables are linked through certain linear constraints. In such a case cell suppressions must obviously be coordinated between tables. In this paper we investigate into the possibilities for an extension of the modular approach to deal with linked tables.

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References

  1. Cox, L.: Disclosure Risk for Tabular Economic Data. In: Doyle, L., Theeuwes, Z. (eds.) Confidentiality, Disclosure, and Data Access: Theory and Practical Applications for Statistical Agencies. North-Holland, Amsterdam (2001)

    Google Scholar 

  2. De Wolf, P.P.: HiTaS: A Heustic Approach to Cell Suppression in Hierarchical Tables. In: Domingo-Ferrer, J. (ed.) Inference Control in Statistical Databases. LNCS, vol. 2316. Springer, Heidelberg (2002)

    Google Scholar 

  3. De Wolf, P.P.: Cell suppression in a special class of linked tables. In: Joint ECE/Eurostat Worksession on Statistical Confidentiality in Manchester (December 2007), http://epp.eurostat.ec.europa.eu/portal/page?_pageid=3154,70730193,3154_70730647&_dad=portal&_schema=PORTAL

  4. Fischetti, M., Salazar Gonzales, J.J.: Models and Algorithms for Optimizing Cell Suppression in Tabular Data with Linear Constraints. Journal of the American Statistical Association 95, 916 (2000)

    Article  Google Scholar 

  5. Fischetti, M., Salazar Gonzales, J.J.: A Unified Mathematical Programming Framework for different Statistical Disclosure Limitation Mehtods. Operations Research 53(5), 819–829 (2005)

    Article  MathSciNet  Google Scholar 

  6. Hundepool, A., van de Wetering, A., Ramaswamy, R., de Wolf, P.P., Giessing, S., Fischetti, M., Salazar, J.J., Castro, J., Lowthian, P.: τ-ARGUS users’s manual, version 3.1 (2006)

    Google Scholar 

  7. Hundepool, A., Domingo-Ferrer, J., Franconi, L., Giessing, S., Lenz, R., Longhurst, J., Nordholt, E.S., Seri, G., De Wolf, P.-P.: CENEX handbook on Statistical Disclosure Control, CENEX-SDC project (2006), http://neon.vb.cbs.nl/cenex/CENEX-SDC_Handbook.pdf

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Josep Domingo-Ferrer Yücel Saygın

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© 2008 Springer-Verlag Berlin Heidelberg

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de Wolf, PP., Giessing, S. (2008). How to Make the τ-ARGUS Modular Method Applicable to Linked Tables. In: Domingo-Ferrer, J., Saygın, Y. (eds) Privacy in Statistical Databases. PSD 2008. Lecture Notes in Computer Science, vol 5262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87471-3_4

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  • DOI: https://doi.org/10.1007/978-3-540-87471-3_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87470-6

  • Online ISBN: 978-3-540-87471-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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